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iSQI Exam CT-AI Topic 5 Question 17 Discussion

Actual exam question for iSQI's CT-AI exam
Question #: 17
Topic #: 5
[All CT-AI Questions]

Written requirements are given in text documents, which ONE of the following options is the BEST way to generate test cases from these requirements?

SELECT ONE OPTION

Show Suggested Answer Hide Answer
Suggested Answer: A

When written requirements are given in text documents, the best way to generate test cases is by using Natural Language Processing (NLP). Here's why:

Natural Language Processing (NLP): NLP can analyze and understand human language. It can be used to process textual requirements to extract relevant information and generate test cases. This method is efficient in handling large volumes of textual data and identifying key elements necessary for testing.

Why Not Other Options:

Analyzing source code for generating test cases: This is more suitable for white-box testing where the code is available, but it doesn't apply to text-based requirements.

Machine learning on logs of execution: This approach is used for dynamic analysis based on system behavior during execution rather than static textual requirements.

GUI analysis by computer vision: This is used for testing graphical user interfaces and is not applicable to text-based requirements.


Contribute your Thoughts:

Laquita
2 months ago
Natural language processing? That's a fancy way of saying 'reading the requirements', but I'll take it over trying to decipher spaghetti code any day!
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Carlota
11 days ago
User 3: Yeah, reading requirements is definitely easier than dealing with messy code.
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Ashley
12 days ago
User 2: I agree, it's much better than analyzing source code.
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Donte
1 months ago
User 1: Natural language processing sounds like a good way to generate test cases.
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Theron
2 months ago
GUI analysis by computer vision? Whoa, we're living in the future! Might as well just let the robots do all the work.
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Felix
22 days ago
C) Machine learning on logs of execution
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Louann
23 days ago
B) Analyzing source code for generating test cases
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Fletcher
1 months ago
A) Natural language processing on textual requirements
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Verona
2 months ago
Machine learning on logs? What is this, a data science exam? I'll stick to the good ol' computer vision, thank you very much.
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Stephaine
2 months ago
Analyzing source code? Nah, that's for the developers, not the testers. Give me that NLP magic!
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Lizette
28 days ago
I think NLP is the best option for generating test cases from written requirements.
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Steffanie
1 months ago
NLP can really help testers understand and create test cases efficiently.
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Sommer
1 months ago
Yeah, analyzing source code seems more like a developer task.
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Misty
2 months ago
I agree, NLP is the way to go for generating test cases from text documents.
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Jeannetta
2 months ago
Yeah, analyzing source code is more for developers, testers should stick to NLP for test case generation.
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Corazon
2 months ago
I agree, NLP is the way to go for generating test cases from text documents.
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Apolonia
2 months ago
I think B) Analyzing source code for generating test cases is the most accurate method.
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Malcolm
2 months ago
I personally prefer D) GUI analysis by computer vision for generating test cases.
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Coral
3 months ago
Natural language processing on textual requirements? Sounds like the way to go, straight from the source!
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Bobbye
2 months ago
That's an interesting approach too, using data from actual executions.
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Malissa
2 months ago
C) Machine learning on logs of execution
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Catrice
2 months ago
Definitely! It helps in understanding the requirements better.
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Yolande
2 months ago
A) Natural language processing on textual requirements
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Alease
3 months ago
I disagree, I believe C) Machine learning on logs of execution is more effective.
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Isidra
3 months ago
I think the best way is A) Natural language processing on textual requirements.
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